This project looks at the effects of COVID-19 on unemployment in Washington and the United States as a whole. This topic is important as the quarantine has had a large impact on the local and national economy.
The data for this project was acquired from the following sources:
We were curious to see which was the most impacted industry based on the unemployment claims made in week 19. We felt this was an important observation to make as identifying the industry that was affected the most can lead to informed decision making when figuring out who should receive the most financial support. The most impacted industry was found to be Educational services.
Next, we wanted to know which industries in King County were the most negatively impacted by the quarantine. We decided to observe this because again, knowing which industries were most negatively affected can help make informed decisions about which sectors need the most financial support. The 5 most negatively impacted industries were: Not disclosed, Educational services, Professional and technical services, Publishing Industries (except internet) and Hospitals.
This aggregate summary table is based on data collected from data source 1. The data in this table is grouped by date, arranged from the most recent date to the earliest date in record. Grouping the data by date allows us to observe the trend of total positive cases in the US every day and we can develop a more holistic understanding of the impact of the virus by also considering the number of people who recovered or are currently hospitalized.
The table includes information of date observed, total positive cases for a given day, total number of people hospitalized/recovered and the total increase in positive cases compared to the previous day.
It can be observed that at the beginning, the number of positive cases grew by a lot every day at a very fast rate. In April the number of cases stabilized at an average of about 30k every day, while in May this number has lessened to about an average of 24k with the most recent data from May 11th marking about an 18k increase in new cases, showing a slowed growth as time goes on.
| Date | Positive Cases | People Hospitalized | People Recovered | Increase in Positive Cases (Compared to Previous Day) |
|---|---|---|---|---|
| 2020-05-11 | 1340412 | 44191 | 232733 | 17605 |
| 2020-05-10 | 1322807 | 44943 | 216169 | 21712 |
| 2020-05-09 | 1301095 | 46637 | 212534 | 25179 |
| 2020-05-08 | 1275916 | 47718 | 198993 | 27779 |
| 2020-05-07 | 1248137 | 49130 | 195036 | 27580 |
| 2020-05-06 | 1220557 | 50227 | 189910 | 24952 |
| 2020-05-05 | 1195605 | 50906 | 189791 | 22152 |
| 2020-05-04 | 1173453 | 50062 | 187180 | 21447 |
| 2020-05-03 | 1152006 | 50312 | 180152 | 26287 |
| 2020-05-02 | 1125719 | 51734 | 175382 | 30038 |
| 2020-05-01 | 1095681 | 52370 | 164015 | 33178 |
| 2020-04-30 | 1062503 | 53793 | 154991 | 29346 |
| 2020-04-29 | 1033157 | 54930 | 147484 | 27020 |
| 2020-04-28 | 1006137 | 54940 | 139342 | 25003 |
| 2020-04-27 | 981134 | 54971 | 121609 | 20791 |
| 2020-04-26 | 960343 | 55050 | 116801 | 27033 |
| 2020-04-25 | 933310 | 56344 | 112783 | 35991 |
| 2020-04-24 | 897319 | 56075 | 101517 | 34196 |
| 2020-04-23 | 863123 | 57889 | 97121 | 31749 |
| 2020-04-22 | 831374 | 58130 | 93157 | 28602 |
| 2020-04-21 | 802772 | 58579 | 73002 | 25942 |
| 2020-04-20 | 776830 | 55677 | 69636 | 25184 |
| 2020-04-19 | 751646 | 55570 | 67339 | 27599 |
| 2020-04-18 | 724047 | 56591 | 62961 | 28037 |
| 2020-04-17 | 696010 | 57808 | 53644 | 31881 |
| 2020-04-16 | 664129 | 58625 | 48945 | 31017 |
| 2020-04-15 | 633112 | 59260 | 43522 | 30317 |
| 2020-04-14 | 602795 | 58719 | 39347 | 25920 |
| 2020-04-13 | 576875 | 55295 | 35442 | 24969 |
| 2020-04-12 | 551906 | 54749 | 34151 | 28013 |
| 2020-04-11 | 523893 | 54757 | 31631 | 31045 |
| 2020-04-10 | 492848 | 51745 | 29054 | 34588 |
| 2020-04-09 | 458260 | 49826 | 24869 | 34215 |
| 2020-04-08 | 424045 | 44063 | 21141 | 30171 |
| 2020-04-07 | 393874 | 42294 | 18477 | 30409 |
| 2020-04-06 | 363465 | 34663 | 16584 | 28747 |
| 2020-04-05 | 334718 | 30905 | 14542 | 25966 |
| 2020-04-04 | 308752 | 29095 | 12840 | 33518 |
| 2020-04-03 | 275234 | 24564 | 10861 | 31999 |
| 2020-04-02 | 243235 | 21833 | 8586 | 28058 |
| 2020-04-01 | 215177 | 19982 | 7084 | 25179 |
| 2020-03-31 | 189998 | 17856 | 5666 | 24477 |
| 2020-03-30 | 165521 | 15574 | 4560 | 21224 |
| 2020-03-29 | 144297 | 13833 | 4061 | 19482 |
| 2020-03-28 | 124815 | 12179 | 3148 | 19353 |
| 2020-03-27 | 105462 | 10789 | 2422 | 18673 |
| 2020-03-26 | 86789 | 7617 | 97 | 17316 |
| 2020-03-25 | 69473 | 4971 | 147 | 12294 |
| 2020-03-24 | 57179 | 3828 | 0 | 10166 |
| 2020-03-23 | 47013 | 2770 | 0 | 10679 |
| 2020-03-22 | 36334 | 2155 | 0 | 8967 |
| 2020-03-21 | 27367 | 1436 | 0 | 6533 |
| 2020-03-20 | 20834 | 1042 | 0 | 5771 |
| 2020-03-19 | 15063 | 617 | 0 | 4198 |
| 2020-03-18 | 10865 | 416 | 0 | 2611 |
| 2020-03-17 | 8254 | 325 | 0 | 2123 |
| 2020-03-16 | 6131 | 0 | 0 | 1280 |
| 2020-03-15 | 4842 | 0 | 0 | 1101 |
| 2020-03-14 | 3741 | 0 | 0 | 737 |
| 2020-03-13 | 3004 | 0 | 0 | 862 |
| 2020-03-12 | 2142 | 0 | 0 | 462 |
| 2020-03-11 | 1672 | 0 | 0 | 392 |
| 2020-03-10 | 1280 | 0 | 0 | 267 |
| 2020-03-09 | 1013 | 0 | 0 | 292 |
| 2020-03-08 | 721 | 0 | 0 | 183 |
| 2020-03-07 | 538 | 0 | 0 | 148 |
| 2020-03-06 | 387 | 0 | 0 | 109 |
| 2020-03-05 | 275 | 0 | 0 | 65 |
| 2020-03-04 | 207 | 0 | 0 | 36 |
| 2020-03-03 | 94 | 0 | 0 | 41 |
| 2020-03-02 | 53 | 0 | 0 | 13 |
| 2020-03-01 | 40 | 0 | 0 | 12 |
| 2020-02-29 | 18 | 0 | 0 | 9 |
| 2020-02-28 | 9 | 0 | 0 | 7 |
| 2020-02-27 | 2 | 0 | 0 | 0 |
| 2020-02-26 | 2 | 0 | 0 | 0 |
| 2020-02-25 | 2 | 0 | 0 | 0 |
| 2020-02-24 | 2 | 0 | 0 | 0 |
| 2020-02-23 | 2 | 0 | 0 | 0 |
| 2020-02-22 | 2 | 0 | 0 | 0 |
| 2020-02-21 | 2 | 0 | 0 | 0 |
| 2020-02-20 | 2 | 0 | 0 | 0 |
| 2020-02-19 | 2 | 0 | 0 | 0 |
| 2020-02-18 | 2 | 0 | 0 | 0 |
| 2020-02-17 | 2 | 0 | 0 | 0 |
| 2020-02-16 | 2 | 0 | 0 | 0 |
| 2020-02-15 | 2 | 0 | 0 | 0 |
| 2020-02-14 | 2 | 0 | 0 | 0 |
| 2020-02-13 | 2 | 0 | 0 | 0 |
| 2020-02-12 | 2 | 0 | 0 | 0 |
| 2020-02-11 | 2 | 0 | 0 | 0 |
| 2020-02-10 | 2 | 0 | 0 | 0 |
| 2020-02-09 | 2 | 0 | 0 | 0 |
| 2020-02-08 | 2 | 0 | 0 | 0 |
| 2020-02-07 | 2 | 0 | 0 | 1 |
| 2020-02-06 | 1 | 0 | 0 | 0 |
| 2020-02-05 | 1 | 0 | 0 | 0 |
| 2020-02-04 | 1 | 0 | 0 | 0 |
| 2020-02-03 | 1 | 0 | 0 | 0 |
| 2020-02-02 | 1 | 0 | 0 | 0 |
| 2020-02-01 | 1 | 0 | 0 | 0 |
| 2020-01-31 | 1 | 0 | 0 | 0 |
| 2020-01-30 | 1 | 0 | 0 | 0 |
| 2020-01-29 | 1 | 0 | 0 | 0 |
| 2020-01-28 | 1 | 0 | 0 | 0 |
| 2020-01-27 | 1 | 0 | 0 | 0 |
| 2020-01-26 | 1 | 0 | 0 | 0 |
| 2020-01-25 | 1 | 0 | 0 | 0 |
| 2020-01-24 | 1 | 0 | 0 | 0 |
| 2020-01-23 | 1 | 0 | 0 | 0 |
| 2020-01-22 | 1 | 0 | 0 | 0 |
This is an area plot chart showing the relationship between the increase in positive cases and number of people currently hospitalized against date. This chart was intended to present the total increase in daily positive cases and currently hospitalized cases from Jan. 23 to May 11. Visualizing this information can help us more easily identify the trend of positive cases and currently hospitalized cases measured daily, and allow us to anticipate the potential trends in unemployment.
=======This is an area plot chart showing the relationship between the increase in positive cases and number of people currently hospitalized against date. This chart was intended to present the total increase in daily positive cases and currently hospitalized cases from Jan. 23 to May 11. Visualizing this information can help us more easily identify the trend of positive cases and currently hospitalized cases measured daily, and allow us to anticipate the potential trends in unemployment.
>>>>>>> Stashed changesThis is a line graph showing the average unemployment claims made in the US, and represents the relationship between the number of initial claims filed on a given date. It is important to observe this information because it allows us to see when the COVID-19 outbreak started to impact the unemployment rates across the country, and this information can be used for instnace to prepare against the next wave of the outbreak to better manage the provision of support for those who become unemployed.
This plot is a plot of initial claims spanning every industry of every county in Washington that occurred on a weekly basis from weeks 1-19 of the pandemic. After week 10 there has been a surge in the number of initial claims made, jumping from 14154 claims in week 10 to 128962 claims in week 11. From weeks 1-10, the trend stayed primarily constant ranging from about 5000-14000, however, after the spike from week 11, the trend has been very sporadic, as intial claims have fluctuated up and down. The use of a scatterplot is used to show if there is a relationship between two numeric variables and to see if there is any possible correlation. To test to see if weeks and initial cases had correlation (that is as one goes through the weeks of the pandemic, it would be apparent that there is a relationship between week and cases), however to this point, it seems as if there is no relationship or a correlation between the two factors.
<<<<<<< Updated upstream ======= >>>>>>> Stashed changes